Real-time automatic multi-style license plate detection in videos

Asmaa Elbamby, E. Hemayed, D. Helal, M. Rehan
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引用次数: 11

Abstract

Despite License Plate Recognition is mainly regarded as a solved problem; most of the techniques have been mainly developed for specific country or special formats which can strictly limits their applicability. There have been extensive studies of license plate detection since the 70s. The suggested approaches have difficulties in processing high-resolution imagery in real-time. This paper presents a novel algorithm for real-time automatic multi-style license plate detection in videos. The proposed algorithm can detect in a real time multiple license plates with various sizes in unfamiliar and complex environment. In this system, candidate plate regions are extracted using a preprocessing function to increase accuracy while decreasing computational time. Then a tree of LBP-based cascade classifiers is used to classify the candidate plate regions into one of the learned style. The proposed approach has been applied to Egyptian license plates with four different plate styles. The proposed approach achieved a success rate of 94% at 25 frames/sec using a moderate laptop.
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实时自动多风格车牌检测视频
尽管车牌识别主要是一个已解决的问题;大多数技术主要是针对特定国家或特殊格式开发的,这严格限制了其适用性。自上世纪70年代以来,人们对车牌检测进行了广泛的研究。所提出的方法在实时处理高分辨率图像方面存在困难。提出了一种视频中实时自动多样式车牌检测的新算法。该算法可以在不熟悉的复杂环境中实时检测多个不同大小的车牌。在该系统中,使用预处理函数提取候选板区域,以提高精度,同时减少计算时间。然后使用基于lbp的级联分类器树将候选板块区域分类为学习到的样式之一。拟议的方法已应用于四种不同车牌样式的埃及车牌。所提出的方法在一台中等的笔记本电脑上以25帧/秒的速度实现了94%的成功率。
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